Multi-Output Sequential Deep Learning Model for Athlete Force Prediction on a Treadmill Using 3D Markers
Por:
Candela-Leal M.O., Gutiérrez-Flores E.A., Presbítero-Espinosa G., Sujatha-Ravindran A., Ramírez-Mendoza R.A., Lozoya-Santos J.J., Ramírez-Moreno M.A.
Publicada:
1 ene 2022
Resumen:
Reliable and innovative methods for estimating forces are critical aspects of biomechanical sports research. Using them, athletes can improve their performance and technique and reduce the possibility of fractures and other injuries. For this purpose, throughout this project, we proceeded to research the use of video in biomechanics. To refine this method, we propose an RNN trained on a biomechanical dataset of regular runners that measures both kinematics and kinetics. The model will allow analyzing, extracting, and drawing conclusions about continuous variable predictions through the body. It marks different anatomical and reflective points (96 in total, 32 per dimension) that will allow the prediction of forces (N) in three dimensions (Fx, Fy, Fz ), measured on a treadmill with a force plate at different velocities (2.5 m/s, 3.5 m/s, 4.5 m/s). In order to obtain the best model, a grid search of different parameters that combined various types of layers (Simple, GRU, LSTM), loss functions (MAE, MSE, MSLE), and sampling techniques (down-sampling, up-sampling) helped obtain the best performing model (LSTM, MSE, down-sampling) achieved an average coefficient of determination of 0.68, although when excluding Fz it reached 0.92. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Filiaciones:
Candela-Leal M.O.:
Mechatronics Department, School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, NL, Monterrey, 64849, Mexico
Gutiérrez-Flores E.A.:
Mechatronics Department, School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, NL, Monterrey, 64849, Mexico
Presbítero-Espinosa G.:
Mechatronics Department, School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, NL, Monterrey, 64849, Mexico
Sujatha-Ravindran A.:
Independent Researcher, California City, CA 94022, United States
Ramírez-Mendoza R.A.:
Mechatronics Department, School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, NL, Monterrey, 64849, Mexico
Lozoya-Santos J.J.:
Mechatronics Department, School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, NL, Monterrey, 64849, Mexico
Ramírez-Moreno M.A.:
Mechatronics Department, School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, NL, Monterrey, 64849, Mexico
All Open Access; Gold
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